Machine cutting tool condition monitoring system of aeroplane material processing based on cellular neural networks

2012 ◽  
Author(s):  
Xiaolin Liu ◽  
Kun Yuan
Keyword(s):  
Neural Networks ◽  
Material Processing ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Cellular Neural Networks ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
Condition Monitoring System

TOOL CONDITION MONITORING SYSTEM IN SERIAL PRODUCTION CONDITIONS

2020 ◽  
Vol 4 (2) ◽  
pp. 161-168
Author(s):  
V.I. GOLOVIN ◽  
S.Yu. RADCHENKO
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Serial Production ◽  
Tool Condition ◽  
Decision Making System ◽  
Software And Hardware ◽  
Condition Monitoring System ◽  
The Cost

One of the most important tasks of serial and mass production is to maintain the continuity of the technological process in order to reduce equipment downtime and, as a result, the cost of production. One of the systems is the tool condition monitoring system. However, the solutions used today are complex software and hardware systems that are not available for most medium and small productions. The article proposes a system based on a comparative analysis of the applied tool with reference instances. The results of the analysis are sent to the decision-making system, which determines the feasibility of further use of the cutting tool for subsequent machining. An example of an experimental study of milling processing is given. The results obtained show the possibility and rationality of using this model to predict the state of the instrument.

Machine Cutting Tool Condition Monitoring Method of Aeroplane Composite Material Processing

2013 ◽  
Vol 411-414 ◽  
pp. 1610-1615
Author(s):  
Xiao Lin Liu ◽  
Chun Yu Mu ◽  
Jian Ting Wang ◽  
Kun Yuan
Keyword(s):  
Neural Networks ◽  
Material Processing ◽  
Computer Vision ◽  
Composite Material ◽  
Cutting Tool ◽  
Cellular Neural Networks ◽  
Tool Condition Monitoring ◽  
Median Filtering ◽  
Monitoring Method ◽  
Tool Condition

Because that the wear of the machine cutting tool of the aeroplane composite material processing is difficult to be monitored, in this paper a monitoring method based on the cellular neural networks by the computer vision monitoring is proposed. The method uses the median filtering technology and the cellular neural networks for the image denoising and the edge detection. Then the degree of the tool wear is judged by calculating the wear characteristic value of the cutting tool. The experimental results show that the system is rational and effective.

scholarly journals Algorithm of the tool condition monitoring system based on many neural networks

Mechanik ◽  
2017 ◽  
Vol 90 (3) ◽  
pp. 220-223
Author(s):  
Sebastian Bombiński ◽  
Joanna Kossakowska
Keyword(s):  
Neural Networks ◽  
Tool Wear ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Machining Process ◽  
Rbf Neural Networks ◽  
Standard Time ◽  
Tool Condition ◽  
Condition Monitoring System

Presented is a comparison of different methods of estimating tool wear – obtained for group of RBF neural networks, hierarchical methods and the standard time counting. The analysis of the signals from the machining process carried out for three different experiments, clearly demonstrating the effect of presented methods. The results obtained for group of RBF neural networks are similar to results obtained for hierarchical methods.

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